Function to run the weighted pDPA algorithm (Rigaill 2010 and 2015) without storing the set of last changes. It only return the cost in 1 to Kmax changes. It uses functional pruning and segment neighborhood. It optimizes the weighted L2-loss (\(w_i (x_i - \mu)2\)) for 1 to Kmax changes.
Usage
Fpsn_w_nomemory(x, w, Kmax, mini = min(x), maxi = max(x))
Arguments
x
a numerical vector to segment
w
a numerical vector of weights (values should be larger than 0).
Kmax
max number of segments (segmentations in 1 to Kmax segments are recovered).
mini
minimum mean segment value to consider in the optimisation
maxi
maximum mean segment value to consider in the optimisation
Value
return a list with the costs J.est in 1 to Kmax changes.